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Research map / Detection and segmentation / CNN features

Non-Local Deep Features for Salient Object Detection

CVPR 2017 · Detection and segmentation › CNN features · approach: RGB salient object detection · 660 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
add the boundary IoU loss to cross-entropy training (ablation)NLDF · HKU-ISmax Fβ: 0.874 -> 0.902Helped
add the boundary IoU loss to cross-entropy training (ablation)NLDF · HKU-ISMAE: 0.060 -> 0.048Helped
add the boundary IoU loss to cross-entropy training (ablation)NLDF · DUT-OMRONmax Fβ: 0.724 -> 0.753Helped
add the boundary IoU loss to cross-entropy training (ablation)NLDF · DUT-OMRONMAE: 0.085 -> 0.080Helped
add the boundary IoU loss to cross-entropy training (ablation)NLDF · PASCAL-Smax Fβ: 0.804 -> 0.831Helped
add the boundary IoU loss to cross-entropy training (ablation)NLDF · PASCAL-SMAE: 0.116 -> 0.099Helped
add the boundary IoU loss to cross-entropy training (ablation)NLDF · ECSSDmax Fβ: 0.886 -> 0.905Helped
add the boundary IoU loss to cross-entropy training (ablation)NLDF · ECSSDMAE: 0.075 -> 0.063Helped
add the boundary IoU loss to cross-entropy training (ablation)NLDF · SODmax Fβ: 0.776 -> 0.810Helped
add the boundary IoU loss to cross-entropy training (ablation)NLDF · SODMAE: 0.161 -> 0.143Helped
add the boundary IoU loss to cross-entropy training (ablation)NLDF · MSRA-Bmax Fβ: 0.912 -> 0.911No clear effect
add the boundary IoU loss to cross-entropy training (ablation)NLDF · MSRA-BMAE: 0.048 -> 0.048No clear effect

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